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cs.IR2024
Tethering Broken Themes: Aligning Neural Topic Models with Labels and Authors
Mayank Nagda, Phil Ostheimer, Sophie Fellenz
Topic models are a popular approach for extracting semantic information from large document collections. However, recent studies suggest that the topics generated by these models o…
cs.LG2024★ 1 cited
SetPINNs: Set-based Physics-informed Neural Networks
Mayank Nagda, Phil Ostheimer, Thomas Specht +5
Physics-Informed Neural Networks (PINNs) solve partial differential equations using deep learning. However, conventional PINNs perform pointwise predictions that neglect dependenci…